Time‐lapse mapping of crop and tillage interactions with soil water using electromagnetic induction

Abstract

Abstract Assessing spatiotemporal variations in soil water is critical to many decisions in precision agriculture. In dryland crop production regions with marginal precipitation, growers use crop rotations and surface preparation practices to build soil water natural capital over preceding seasons for cash crop production. However, significant gaps exist in quantifying linkages between topography, soil properties, and site‐specific agronomic practices to crop water use, and to predict temporal changes in soil water storage. In this study, we used time‐lapse electromagnetic induction to measure apparent electrical conductivity (ECa) to infer spatiotemporal variability of soil water while comparing crop (winter wheat [Triticum aestivum L.], spring peas [Pisum sativum L.], and spring barley [Hordeum vulgare L.]) as well as tillage (no till and chisel plow) on a split‐plot design in the Palouse region of northern Idaho. Weekly measurements of ECa were converted to soil water content using multiple linear regression with the help of principal component analysis. Separating factors of temporal stability and variability allowed us to derive crop‐specific calibrated relationships between soil water content and the additional variables growing degree days, elevation, clay content, and silt content. Results suggest that spring peas retained the highest water content, followed by spring barley and winter wheat. Resultant maps show highly structured and consistent patterns in ECa being driven primarily by crop type that are apparent even in uncalibrated imagery. Although soil ECa tended to be greater in no‐tillage compared with chisel plow treatments, we found no significant differences in soil water content between the two. This may be partially due to the limited number of years of no‐till practice at this site.